A guide to creating a custom IPython magic command that enables Ruby code execution within Google Colab notebooks, bypassing previous integration issues.
Explains the history and differences between IPython, Jupyter Notebook, JupyterLab, and related terms in the Python data science ecosystem.
A troubleshooting guide for fixing the 'java.lang.ClassNotFoundException: delta.DefaultSource' error when using Delta Lake with PySpark in Jupyter.
A guide on how to launch and access a Jupyter server directly within a Dask cluster running on Kubernetes, including configuration steps.
A hands-on tutorial exploring LakeFS for data versioning and branching using PySpark and Jupyter notebooks in a data engineering context.
A review of Python tools and libraries for visualizing and interactively exploring Pandas DataFrames, comparing them to Excel's graphical interface.
An introduction to scientific computing in Python using NumPy for numerical arrays and Matplotlib for data visualization.
A guide to streamlining ML experiments by combining Jupyter, Papermill, and MLflow for parameterized runs and centralized logging.
A guide to setting up Jupyter Lab to launch automatically on macOS startup using a LaunchAgent .plist file.
A guide to creating, installing, and using IPython extensions to customize and enhance the IPython interactive shell.
A tutorial on creating custom cell magic functions in IPython, focusing on building a type-checking helper using Python's type hints.
Explores how Jupyter notebooks can be used for infrastructure tasks like system administration, DevOps, and cloud operations, blending documentation, code, and output.
A video series on transitioning from interactive Jupyter data exploration to reproducible, packaged, and tested code for data analysis.
A guide to creating presentation slides using Jupyter Notebook and Reveal.js, including automation and hosting on GitHub Pages.
A developer revives the Vega.jl package for Julia, updating it for v0.4, adding Jupyter Notebook support, and planning new visualizations.
Exploring the IBash Notebook, a Bash kernel for Jupyter, and its potential as a data science environment with inline image support.
A tutorial on creating tables of contents with internal links in IPython Notebooks and Markdown documents using HTML anchors.
Introducing ipywidgets, a library for creating static, interactive widgets in IPython/Jupyter notebooks that work without a live kernel.
Two methods to add line numbers to cells in IPython/Jupyter Notebooks: a keyboard shortcut toggle and a permanent startup configuration.
Explains how to pass data between Javascript and Python in IPython/Jupyter notebooks using kernel.execute, though notes the method is now obsolete.
